Retirees' health insurance cut off as companies change. - Saint Paul Pioneer Press (St. Paul, MN)

Byline: Gail MarksJarvis

ST. PAUL, Minn. _ Ed Stish is not living the carefree life he envisioned when he retired from a taconite mine in Keewatin, Minn., three years ago. He has no time for lounging in a La-Z-Boy, golfing or fishing for pleasure.

Instead, Stish rises early and sets about growing vegetables, trapping beaver for pelts and harvesting wild rice on a lake near his home in Bovey. His wife, Sue, sells the bounty at farmers' markets four days a week.

They do this to survive. Just a few months after he retired at age 50 from National Steel Corp., his employer of 30 years went bankrupt, taking with it longtime promises to provide a livable pension and cheap health insurance for life.

Even though the U.S. Pension Benefit Guaranty Corp. stepped in to protect workers' pensions, Stish's monthly payment was cut almost in half to $1,350. And the buyer of the mine, U.S. Steel, never made good on the old promise to provide retiree health insurance.

That left Stish in the same predicament as countless retirees caught in an unaffordable health insurance trap they never expected. Company-paid health insurance for retirees is becoming extinct as companies try to slash costs and increase profits.

While federal law requires companies to deliver the pensions they promised workers, no such legal obligation exists for health insurance.

Eleven years ago, 46 percent of large U.S. companies helped retirees with health insurance, but now just 28 percent continue to do so, says researcher Paul Fronstin of the Employee Benefits Research Institute. Among all U.S. companies, 11 percent provide retirees with health insurance.

Fronstin says current workers of any age should not expect the benefit when they retire unless they work in some government jobs or are protected by a union contract guaranteeing coverage. His warning allows people who still have jobs to plan for their future, but retirees don't have the luxury of time or a paycheck.

In the past few years, retirees like Stish were taken by surprise when an employer went broke or was acquired by another company that didn't want to continue their health benefits. Others have lost insurance because former employers wanted to avoid spiraling health insurance costs, or they could bolster corporate profits quickly through an accounting maneuver that can turn disbanded insurance liabilities into instant income.

Last year, 10 percent of companies that gave retirees health benefits eliminated them completely and 71 percent made retirees pay a greater portion of health coverage, according to research by the Kaiser Foundation and Hewitt Associates.

(EDITORS: BEGIN OPTIONAL TRIM)

'There is no way people could have anticipated the rate of inflation in health care, and no way for a person to plan if the trend continues,' says Michael Stein, a Boulder, Colo., financial planner and author of 'The Prosperous Retirement.' 'It's a societal crunch, and society will have to make changes.'

(END OPTIONAL TRIM)

Cutting retiree benefits is considered the path of least resistance _ considerably easier than upsetting existing workers with benefit cuts or disappointing shareholders with lackluster profits. The special accounting attached to cuts in health benefits works almost magically to prop up corporate profits, even if a company has not sold more goods or services.

'Companies attack the segment of their stakeholders that have no defense,' says Jim Norby of the National Retirees Legislative Network.

The network has asked Congress to pass laws that would mandate employers to maintain their commitments to retirees, but Norby says there's not much interest.

Fronstin says policy makers could also address the erosion of retiree health benefits by expanding Medicare or other programs covering such expenses, changing tax treatment for health expenses and educating people that they must save for retirement health insurance.

Meanwhile, as companies slash benefits, retirees are left in a bind. With poor job prospects and insurance costs high for older people, many retirees can't afford thousands of dollars in unexpected expenses.

Typically, when workers consider retirement, they check on their company benefits and add up monthly living expenses ranging from heat to property taxes. If pensions, savings and Social Security look like they will cover all the costs, they may decide it's safe to retire.

But that can be a serious mistake if unanticipated health insurance costs pop up after retirement. Early retirees, those younger than 65, may have to spend $1,000 a month for insurance. People eligible for the federal Medicare program may have to spend about $250 a month on supplemental insurance because Medicare only covers about half of the costs.

An individual who retired in 2003 with employer health benefits will need between $37,000 and $750,000 in savings to pay for his supplement to Medicare, according to the Employee Benefits Research Institute. An individual without any help from an employer will need $47,000 to about $1.5 million.

Stish never considered this before he retired. Throughout his years as a mechanic in the taconite mine, he believed the company would give him cheap lifetime insurance if he just completed 30 years of work.

'Instead, I was just cast in the wind,' he says.

(EDITORS: BEGIN OPTIONAL TRIM)

To keep costs down, Stish insured his wife and himself but not a healthy daughter still living at home.

He figured he couldn't skip insurance because he and his wife have high blood pressure. Plus, he retired at 50 after his doctor warned him: 'You've got to quit, or you are going to die.'

But he can't afford much insurance. His policy will cover an expensive emergency, but each year he must pay the first $5,000 of the couple's expenses for doctors, hospitals and medicine. Besides that, he pays $750 every three months for health insurance.

That takes a big chunk out of his $1,350 monthly pension. Stish worries what will happen if his body no longer allows him to work and health insurance costs keep climbing 15 percent a year.

(END OPTIONAL TRIM)

(EDITORS: BEGIN OPTIONAL TRIM)

That threat also troubles Tom Bedford, a retired IBM engineer in Arden Hills, Minn.

In 1991, Bedford retired at age 61 from IBM specifically because he wanted a benefit that was scheduled to disappear if he waited another year _ the promise of free health insurance for life.

Despite that understanding, Bedford recently started picking up health care costs. At age 74, he must pay $100 a month for health insurance and the first $2,000 in medical expenses each year that he and his wife incur.

He can afford that now, but says 'it would be terrible if the insurance rose to $300 or $400.' Since both his parents and his wife's parents lived to their mid-90s, he knows he could far outlive his ability to work or pay the likely increases in insurance.

'I guess it's just a matter of time before the bomb is going to drop,' Bedford says.

He says he didn't consider this possibility the day he retired because 'IBM had such a good health plan you never had to worry.'

IBM says it still offers a good health plan. 'If you look at our competitors, you'll see that IBM continues to offer some of the most generous retiree medical subsidies in the industry,' says spokeswoman Kendra Collins.

(END OPTIONAL TRIM)

Rodney Peterson also didn't think he'd have a health care worry when he retired 21 years ago from Northwestern Bell in Duluth, Minn. His employer guaranteed coverage for life. But now he's paying about $800 a year, and at 81, he can't work for the extra money.

That's part of his problem. Two years ago, he moved from his home in Duluth to an apartment in Rice Lake, Wis., because he could no longer keep up a house and routine paperwork. He needed to be near a daughter in Wisconsin who could help him.

After his move, Qwest _ which had acquired the former Northwestern Bell _ told him he'd have to pay more for insurance in Wisconsin than he paid in Minnesota. With the extra financial burden, he now wonders how he will afford to fix the brakes on his car.

'I feel like we've been let down,' Peterson says.

Peterson is not the only one feeling that way. Many of Qwest's employees were absorbed from companies Qwest purchased, and their cultures were different, says Dick Caldwell of Arden Hills, Minn., a former speechwriter for Qwest executives.

When people worked for Northwestern Bell, they agreed to work for lower pay than elsewhere, but they did it because the culture promised retirement security _ including lifetime health insurance, says Caldwell.

'They should act honorably and continue paying, rather than letting a threat hang over retirees,' he says of Qwest.

He adds that the extra health costs retirees are now bearing is a slap in the face to those who rallied to Qwest's defense about a year ago.

Qwest wanted to offer long-distance phone service to customers, and the company had to get approval from state regulators. Retirees were called upon to urge regulators to help. They made the plea for Qwest so the company could keep paying pensions and health benefits, Caldwell says.

Just a short time afterward, retirees received what Tom Lee of Hopkins, Minn., calls 'our horrifying Halloween letter.' Mailed in October, the letter from Qwest told some retirees that they would have to start paying 20 percent of their health insurance costs.

Qwest declined an interview for this story, but in a written statement said, 'In an age of ever-increasing benefit costs and an extremely competitive marketplace environment, it has become necessary for Qwest _ like other major U.S. companies including AT&T, BellSouth and SBC _ to modify its benefit plans for retired employees.''

Under an accounting rule, companies are required to book their expenses for future retiree benefits years before the employees leave the company. Then, if the benefits are changed and will cost a company less in the future than earlier anticipated, the company can log the savings as income. The procedure is not one companies publicize, and IBM declined to discuss it.

Most companies are free to cut benefits at will as long as their documents say they might do it, says Minneapolis attorney John Nichols.

But most people planning for retirement don't hunt through the legalese and consequently are taken by surprise.

'I was dumb enough that I didn't read everything,' Lee says. Instead, on the day he retired at age 58, 'I jumped up in the air and clicked my heels.'

___

(c) 2004, Saint Paul Pioneer Press (St. Paul, Minn.).

Visit the World Wide Web site of the Pioneer Press at http://www.twincities.com/mld/pioneerpress/

Distributed by Knight Ridder/Tribune Information Services.

_____

PHOTO (from KRT Photo Service, 202-383-6099): PFP-RETIREMENT

The influences of Taiwan's National Health Insurance on women's choice of prenatal care facility: Investigation of differences between rural and non-rural areas.(Research article)(Survey) - BMC Health Services Research

Authors: Likwang Chen (corresponding author) [1,2]; Chi-Liang Chen [3,4]; Wei-Chih Yang [1]

Background

Although there is some dispute over how prenatal care can improve child health, its potential in this regard is well recognized [1, 2, 3]. It is thought to benefit child health and reduce maternal mortality, and it is thought to be a good vehicle for the delivery of health care, health education, and psychosocial services to women [4, 5]. Ensuring access to adequate prenatal care has been an important task for both developed and developing countries; thus, barriers to the utilization of prenatal care services have attracted much attention from health policy researchers.

Level of utilization of prenatal care has been associated with age, marital status, educational level, occupation, income, higher parity, difficulties in dealing with health service organizations, and health insurance status [6, 7, 8, 9, 10]. It has also been associated with conditions during pregnancy, including gaining excess weight during pregnancy, having a baby for the first time, carrying twins or triplets, being at a higher obstetric risk, being attended to by a doctor rather than other types of caregivers, and switching to another health care facility during pregnancy [6, 10]. Among various factors associated with prenatal care utilization, the provision of public health insurance to cover prenatal care has been a policy instrument of interest to many advanced or newly industrialized countries.

Literature specifically discussing the effect of public health insurance on prenatal care utilization is quite limited. Some studies have found that it has a positive effect. Griffin et al. (1999), comparing enrollees of a Medicaid managed care program in Rhode Island and their counterparts with private insurance, concluded that the implementation of the Medicaid program resulted in significant improvement in adequacy of prenatal care utilization [11]. Chen et al. (2001), using data from two cross-sectional surveys conducted in 1989 and in 1996 to investigate the utilization pattern of prenatal care in Taiwan, found that utilization of expensive prenatal services, such as amniocentesis and German measles testing, was substantially higher in 1996 than in the late 1980s, suggesting that the implementation of the NHI may induce greater demand for expensive prenatal services [12]. In contrast, they also found that from late 1989 to 1996 the proportion of women receiving consultation services remained stable and the proportion of women receiving family planning consultation declined [12].

Results from another study using data from the same Taiwanese cross-sectional surveys showed that Taiwanese women were more likely to receive adequate prenatal care in 1996, one year after the launch of the NHI, than in 1989 [6]. That same study found that before the NHI was inaugurated, female farmers and blue-collar workers used prenatal care services more frequently than women in other occupations, but afterwards female civil servants were the group seeking prenatal care most frequently [6]. It has also been found that Taiwanese women who visited clinics were more likely to receive adequate prenatal care than those visiting hospitals after the NHI started, though this was not found in the late 1980s [6, 10]. However, previous studies have not well investigated the differences in the choice of prenatal care facility and perceived convenience in transportation for acquiring such care between women living in areas with different levels of urbanization in Taiwan.

Since it established its national health insurance program in 1995, Taiwan has stopped using its public health system of community health care centres as the major vehicle of providing free prenatal care, and began to provide it through the NHI system, which allows expectant mothers to seek prenatal care from a variety of healthcare facilities. Before 1995, Taiwan already had three major types of public insurance programs covering about 57% of the population. The Labor Insurance program, launched in 1950, covered employees such as workers of government-run enterprises, private company employees, blue-collar employees and members of professional unions who were over 15 years of age and under 60 years of age. Established in 1958, the Government Employee Insurance (GEI) program, covered officers and full-time employees of government agencies, teaching and administrative staff of government-owned schools and private schools, and retirees from these organizations. In 1988, the Farmer's Insurance program extended coverage to members of farmers' associations and individual farmers who were over 15 years old. The three programs had similar benefits packages, covering outpatient visits, hospitalisation, diagnostic tests and prescription drugs. However, only the GEI program covered dependents, and offered free prenatal care to its enrolees through health care facilities that had contracts with this public health program.

While GEI was the only public health insurance program to provide prenatal care before the launch of the NHI, Taiwan's government had been promoting prenatal care long before the introduction of the NHI system through its public health system of community health care centres. Before 1980, each township had its own health station. Additionally, by recruiting physicians from non-rural areas to support services in rural public health stations, Taiwan's government had strengthened the functions of these public health stations and improved health care resources in remote areas by the mid-1990s. Taiwan's public health stations played an important role in providing health care to people in rural areas. For instance, most Taiwanese people in remote areas thought that the local public health station was the health care facility most close to them [13]. The public health stations also played an important role in disseminating health knowledge in rural areas in the early 1990s. A study in 1991 indicated that the major source of medical information for families in rural areas in Taiwan came from the public health nurses from these stations who made home visits [14]. Through this network of public health stations, Taiwan's government delivered free prenatal care to pregnant women long before the NHI was implemented.

Taiwan's NHI in 1995 substantially extended insurance coverage to all its citizens with an equal and comprehensive benefits package. By the end of 1995, it covered 97% of the population; by 1998, the coverage was over 99%. Since 1995, Taiwan's government has been providing ten free prenatal care visits to each pregnant woman in Taiwan through the NHI delivery system. Almost all hospitals and over 90% of clinics have contracts with the NHI program, and this has substantially expanded women's choice of health care facilities from which they can seek prenatal care. Because of the increase in facilities, it would seem natural that the NHI may substantially reduce the travelling costs for seeking prenatal care. Nevertheless, physician and health facility registration data in the NHI database show that the density of gynaecologists and obstetricians and that of health care facilities providing gynaecologic and the obstetric care were a lot lower in rural areas than non-rural areas, suggesting that the NHI could substantially expand women's prenatal health care choices only in non-rural areas.

There has not been much research on the effect of public health insurance on utilization patterns of prenatal care. What little there is has focused on the number of prenatal care visits made and when they are made. This study compares the differences in how women in rural and non-rural areas chose prenatal care facilities before and after the implementation of the NHI. To do this, we analysed women's responses to a national survey in Taiwan. We focused on their replies to questions about 'the type of major health care facility used,' and 'the convenience of transportation to and from prenatal care facility.' We compared the difference in how they answered these questions for children born before and after the implementation of the NHI.

The first indicator was chosen because it can be related to quality of care. Although many people tend to believe that health care delivered in large hospitals, which are usually better equipped, is better than that provided by clinics, some studies in Taiwan have suggested that one would be more likely to get more adequate prenatal care in a clinic than in a large hospital [6, 10]. The second indicator, 'the convenience of transportation to and from prenatal care facility,' can be related to 'the physical accessibility' to care. This indicator is worthy of investigation, especially for Taiwan, where one of the major goals of its national health insurance program was to improve accessibility to health care.

Results obtained by this investigation may help set future directions of prenatal care provision in Taiwan, and may also be used by countries hoping to improve prenatal care delivery. In particular, Taiwan's case offers a unique opportunity to study the influences of national health insurance on women's choice of prenatal care facility in a situation in which they were once able to receive it free at designated public health facilities but now can seek it in any facility they want to go to as long as it has a contractual agreement with the Bureau of National Health Insurance. Other countries may also face such policy options in the future. Therefore, Taiwan's lesson can be useful to them.

Methods

Study design and data

We wanted to know whether Taiwan's National Health Insurance influenced the aforementioned indicators differently in rural and non-rural areas. We examined what disparities existed in these indicators between women in rural and non-rural areas in various periods before and after the NHI was launched. Specifically, we selected two periods before NHI, which were the early 1990 to 1992 and 1993 to the early 1995, and two periods after NHI, which were 1996 to 1997, and 1998 to 1999.

This study used second-hand data. The data were collected retrospectively from a national face-to-face interview survey conducted by Taiwan's National Health Research Institutes in the latter half of 2000. This national survey, which was for investigating child health and related health care utilization, collected data for two national representative samples - one for children born between March 1 of 1995 and February 28 of 1996 (1,853 children), and the other for children born between March 1 of 1996 and February 28 of 1999 (2,207 children). The survey was administered to the caregivers of these children. The respondents were also asked to report information for these children's siblings born on or after March 1 of 1990. Therefore, the database of this survey included records for children born between 1990 and 2000. The response rate was 76%, with over 98% of the respondents being the children's mothers. In total, the survey collected data for 7,817 children in 3,934 families.

For each child, the survey data include the child's and the mother's demographic background, the socioeconomic conditions of the family, the child's location of residence, and childcare and health care utilization for the child. Regarding the choice of prenatal care facility, the mother was asked to reply the following question: 'What was the name of your major health care facility for acquiring prenatal care during this pregnancy, and in which township was this facility located?' Based on information collected by this question, the interviewer subsequently recorded the type of the health care facility referring to a corresponding database constructed by Taiwan's Department of Health. The mother was further asked to evaluate her perceived convenience of transportation to and from this health care facility, by the following question: 'Was it convenient for you to go to this prenatal care facility?' The corresponding responses were 'very inconvenient,' 'somewhat inconvenient,' 'moderate,' 'convenient,' and 'very convenient.'

We extracted data from this database for our study based on the following criteria. First, we excluded records reported by caregivers other than the mothers. Second, we excluded records for children born between March 1 of 1995 and December 31 of 1995, because the mothers would be pregnant both before and after the NHI was implemented. Third, we also excluded children born in 2000, a special year in Taiwan. It was the start of the new millennium, and also the year of dragon, the preferred year for having babies for Taiwanese, especially male babies. Because this year was not a typical year in Taiwan in terms of the level of fertility as well as the obstetrical care market for years after the mid-1990s, but there were not enough children born in 2000 to form a sub-sample, we excluded cases for 2000. Fourth, we excluded children whose main caregivers in infancy were not the mothers, since we had to use information on the district where a child lived in infancy to construct a proxy variable reflecting the mother's living place during pregnancy. Fifth, we excluded children whose mothers were covered by the GEI during pregnancy, since women with the GEI were a special group with public insurance covering prenatal care in the pre-NHI period.

We were left with 4,820 children after these selection processes. Within these cases, 1,575 were children from mothers who contributed one record each to these 4,820 cases, and the other 3,245 cases were children from mothers who contributed at least two records each to these 4,820 cases. This paper reports results based on data for the 1,575 children, out of a concern regarding correlation among multiple cases from a same woman. While our analytical sample did not end up being a nationally representative sample for children born in these years, it should still be appropriate for this present study, as the focus of this study is based on multivariate statistical analysis, and a rich set of explanatory variables were included in its estimation.

Unfortunately, we did not have a sufficiently large sample size to compare the experiences of prenatal care utilization for a specific cohort before and after the implementation of the NHI. We could only find 168 women who gave a birth between March 1 of 1990 and February 28 of 1995 and another in the period between 1998 and 1999. This prohibited us from comparing a cohort of women's behaviours before the NHI and in the late 1990s.

Sample characteristics

The characteristics for the 1,575 cases are presented in Table 1. As shown in Table 1, in our sample, women who delivered children during the pre-NHI period tended to deliver their first children, and also reported a younger age at delivery. This is related to the data collection process for the NHRI survey, from which we obtained our second-hand research data. To be included in the original sample for this survey, a child born in the pre-NHI period must have had at least one younger sibling born in the post-NHI period. Therefore, the sampled children born in the pre-NHI period were more likely to have a lower birth order than those born after the NHI was implemented, and women in the sample also tended to report a younger age at delivery for children born before the launch of NHI. In our analytical sample, each child born in the pre-NHI period had a younger sibling who was excluded in our sample selection process. Most of such siblings were born between March 1, 1995 and December 31, 1995, and this is related to the reasons why the proportion of males was higher and more children were born in rural areas in the cohort of children born in 1993-1995. Rural women tend to have a shorter space between having their first two births, and appear to have more baby boys. That there were more boys in the sample in years after the mid-1990s is consistent with the facts that the traditional Taiwanese culture has a strong son preference, and that high sex ratios at birth have been observed. There has been some argument over artificial selection of the gender of offspring by medical technology since the 1990s [15, 16].

Table 1 caption: Sample characteristics [table omitted]

For each cohort of children, almost all of their mothers were married in 2000. The proportion of aboriginal or foreign-born mothers was higher for children born after 1995. The proportion of mothers who immigrated to Taiwan from Mainland China was also higher for children born after 1995. This is consistent with the fact that Taiwan has more and more children who have mothers immigrating to Taiwan from Mainland China or some countries in south-eastern Asia. Women who delivered children after 1995 tended to have more education, and those delivering children in the late 1990s tended to have lower family income. This should be related to the fact that the mothers of children born after 1995 tended to be younger than the women delivering children during the pre-NHI period.

Table 2 compares the choices of prenatal care facility of women living in rural areas and those in non-rural areas. These descriptive statistics suggest that women living in rural areas were less likely to choose medical centres or regional hospitals (large hospitals) than women in non-rural areas in the pre-NHI period. However, women in rural areas were more likely to choose large hospitals as their major health facility in the late 1990s than earlier in the 1990s, while women in non-rural areas did not have such a trend. A smaller proportion of women in rural areas perceived very convenient transportation to and from prenatal care facility in the late 1990s than earlier. In contrast, more women in non-rural areas felt that their transportation for acquiring prenatal care was very convenient in years after 1992 than in 1990-1992.

Table 2 caption: The type of major health facility used for prenatal care [table omitted]

Empirical specification and statistical models

This study defined three types of health care facilities, and four levels of the convenience of transportation. (The detailed definitions of the outcome variables can be found in Table 3.) The indicator regarding 'the type of major health care facility used' is a 3-point nominal variable, and we adopted the multinomial model to investigate factors related to this indicator [17]. We used a 4-point ordinal variable as the indicator for 'the convenience of transportation' and applied the ordered probit model in our multivariate analysis [17]. The Huber/White/sandwich estimator was employed to obtain robust variance estimates. This method is a commonly used estimator of standard errors, and it is robust without assuming that the standard errors are independent from the explanatory variables and are identically distributed [18]. We used the Stata Statistical Software for our multivariate analysis.

Table 3 caption: Definitions of the outcome variables and major explanatory variables in multivariate analysis [table omitted]

We specified three major types of explanatory variables - the time period a child was born in, the level of urbanization in the area where a woman resided while being pregnant, and the interaction of these two factors. In addition to these major explanatory variables, we also controlled for a detailed set of other factors: some related to children, and some related to the mother and the family. The child characteristics included gender and birth parity. The maternal characteristics included her age when she bore the child, her abnormal obstetric health problems during this pregnancy, the year when she was born, and her ethnic background. Maternal characteristics also included the number of children she had, and her marital status and educational attainment at the time of the interview. Regarding the family, we included 'the average monthly family income in the year in which a mother was interviewed' as an explanatory variable. Due to data availability, the explanatory variables included a mother's marital status and educational attainment at the time of interview, and the average monthly family income of the year in which the interview was administered, instead of those variables at the time of pregnancy.

The empirical specification used to compare the influences of the NHI on the choice of prenatal care facility between women living in rural areas and those in non-rural areas is as follows:

[math omitted]

Y is one of the two indicators mentioned previously. Xc denotes explanatory variables other than the major ones. 1993_1995, 1996_1997, and 1998_1999 were used to capture the time trend, with the base period being from March 1, 1990 to December 31, 1992. The three interaction terms were for investigating the differences in the time trend between rural women and their counterparts in non-rural areas (The detailed definitions of the major explanatory variables can be found in Table 3).

Estimation of changes in the relative probability of choosing hospitals and in the probability of perceiving very convenient transportation from 1990-1992 to later years in the 1990s

Using coefficients and the corresponding covariance matrices estimated by the multinomial logit model, we calculated the probability of choosing a specific type of setting as the type of major health facility used for prenatal care [17, 19, 20]. We further estimated the relative probability of choosing hospitals to choosing non-hospital settings for each time period, and the changes in the relative probability from 1990-1992 to the three later periods in the 1990s [19, 20].

The relative probability of choosing large hospitals to choosing non-hospital settings was measured as the ratio of the probability of choosing large hospitals to the probability of choosing non-hospital settings. It is exp(

X 'b1 ), where X is the set of all explanatory variables and b1 is the set of coefficients corresponding to the category of visiting medical centres and regional hospitals. Similarly, the relative probability of choosing small hospitals to choosing non-hospital settings is exp(X 'b2 ), where b2 is the set of coefficients corresponding to local hospitals. The change in the relative probability from 1990-1992 to a specific later period was measured as the ratio of the relative probability for that period to the relative probability for 1990-1992. (The formulas for calculating the 95% confidence interval estimates of these changes are presented in the appendix.)

In the ordered probit model, the values of thresholds (or called 'cut points'), together with the values of coefficients, determine the probabilities of falling in various categories of the dependent variable. We used information with respect to coefficients, thresholds and their corresponding covariance matrices to calculate the probability of perceiving very convenient transportation, and estimated the changes in the probability from 1990-1992 to the three later periods in the 1990s [17, 20]. The change from 1990-1992 to a specific later period was measured as the probability for that period minus the probability for 1990-1992. (The formulas for calculating the 95% confidence interval estimates of these changes are in the appendix.)

We needed to select a representative case for calculating the probabilities of choosing a specific type of setting as the type of major health facility used for prenatal care and of perceiving very convenient transportation. Referring to the sample characteristics, we chose the following characteristics for such estimation: the child was male and the first child; the mother bore the child before thirty years old, had no abnormal condition during this pregnancy, and was born before 1970, and her ethnicity was Fu-Chien; she had two children, was married, and had senior high school education and an average monthly family income less than 50,000 Taiwanese dollars when she was interviewed in 2000. Based on these characteristics, we calculated the two kinds of aforementioned probabilities for each time period, and for rural and non-rural women, separately.

Results

Changes in the relative probability of choosing large hospitals from 1990-1992 to later years in the 1990s

The probability of choosing large hospitals for women in rural areas was significantly higher between 1998 and 1999 than between 1990 and 1992 (Table 4). According to the point estimates, for women in rural areas, the relative probability of choosing large hospitals to choosing non-hospital settings in 1998-1999 was 6.54 times of that in 1990-1992. In contrast, their relative probability of choosing local hospitals in 1998-1999 was only 1.92 times of what it was between 1990 and 1992, and it was not statistically significant.

Table 4 caption: The relative probability of choosing hospitals to choosing non-hospital settings as the type of major health facility used for prenatal care [table omitted]

Changes in the probability of perceiving transportation to be very convenient from 1990-1992 to later years in the 1990s

Regarding the changes in the probability that women would perceive transportation to be very convenient from the period between 1990 and 1992 to the three later periods in the 1990s, only the change corresponding to 1998-1999 for women in non-rural areas was statistically significant (Table 5). These women were more likely to feel very convenient transportation during the period between 1998 and 1999 than during the period between 1990 and 1992. For a non-rural woman with representative characteristics mentioned previously, she had a 26.8% probability of perceiving that transportation for obtaining prenatal care was very convenient in non-rural areas between 1990 and 1992, and was 8.4% more likely to find it very convenient there between 1998 and 1999. In contrast, women in rural areas did not have this trend, and might be less likely to perceive very convenient transportation between 1998 and 1999 than between 1990 and 1992. According to our point estimates, for a rural woman with aforementioned characteristics, her probability of perceiving transportation as being very convenient was 34.8% between 1990 and 1992, and she was 14.5% less likely to find it very convenient there between 1998 and 1999. This estimate, however, was marginally insignificant, with its upper bound of the 95% confidence interval slightly larger than 0. If our sample size could be a little larger, we would expect such a difference to be statistically significant.

Table 5 caption: The probability of perceiving very convenient transportation to and from prenatal care facilities [table omitted]

Other factors related to choice of prenatal care facility

Results from our multivariate analysis revealed there were some other factors related to the choice of prenatal care facility (detailed results available upon request). Women with abnormal health conditions were more likely to seek prenatal health care in large hospitals. Women who bore their babies between age 30 and 34, women who were born before 1970, women with higher education and higher family income were also more likely to seek prenatal care in large hospitals.

Discussion

In this study of Taiwanese women's choice of prenatal care facility from the early 1990s to the late 1990s, we found that women in rural areas were more likely to go to large hospitals to obtain prenatal care in the late 1990s than in the early 1990s. Moreover, women in rural areas were less likely to perceive that transportation had improved for acquiring prenatal care in the late 1990s than their counterparts in non-rural areas. Our findings suggest that more effort is necessary to help reduce the disparities between women in rural areas and those in non-rural areas.

Since the launch of NHI, recruiting physicians for certain specialties has been challenging for hospitals and medical professional groups, and recruiting for gynaecologic and obstetric departments have had particularly noticeable difficulties. The NHI payment scheme has generally been regarded as a factor associated with such a problem, as gynaecologists and obstetricians complained that the payment level for them is not as good as those for many other specialists [21]. Another factor making gynaecology and obstetrics become unfavourable specialties is that gynaecologists and obstetricians are more likely to be involved in medical disputes than physicians of many other specialties [21]. In the 1990s, there were quite a few cases in which some pregnant women's or lying-in women's family members went to protest or file lawsuits against their gynaecologists and obstetricians because they were not satisfied with the treatments their doctors provided.

Moreover, business has been dropping for gynaecologists and obstetricians as Taiwan's fertility rate has been dropping since the late 1990s. The total fertility rate in 1997 was 1.77, which was about the same level in the early 1990s, but it dropped to 1.56 in 1999, and further to 1.12 in 2005 [22]. The decrease in fertility is significant in both rural and non-rural areas [22]. Business is also uneven, depending on the years considered favourable for giving birth. For example, fertility was much lower in 1998 because it was a Tiger Year, traditionally considered to be unfavourable in Taiwan, and high in 2000, which is a Dragon Year and very favourable. The quickly decreasing and uneven fertility rate also makes gynaecology and obstetrics less attractive specialties.

Regarding the type of health care facility for obtaining prenatal care, we found that women in rural areas were more likely to seek prenatal care in large hospitals in the late 1990s than earlier in the 1990s, a finding that is consistent with results from one study which showed that a large hospital in Taiwan symbolized good quality care in the 1990s [23]. Taiwan's NHI payment scheme has made hospital owners to prefer to use high technology to have their hospitals re-accredited as large hospitals, so that they have had a tendency to compete on a non-price basis [24]. Since the implementation of the NHI, a substantial proportion of small hospitals have gradually exited the hospital market, and a major competition strategy adopted by hospitals is to expand their sizes and increase the use of high technology devices to signal their quality levels [24]. As health care consumers in Taiwan have no reliable information sources regarding the quality levels of health care facilities, some of them may just use the size of a health facility to judge its quality. Particularly, since it is harder for rural residents to collect information on the quality of health care facilities outside their communities, they might be more likely to judge the health care quality of a facility based on its size.

If women in rural areas believe that a larger size of hospital reflects better quality of health care, and choose to leave their living districts to seek prenatal care, it appears reasonable that they would prefer large hospitals rather than smaller health care facilities. The behaviour of enduring inconvenient transportation was also consistent with the finding shown in one research which reported that time cost was a factor with a low elasticity for utilizing ambulatory care in Taiwan in the 1990s [25]. Moreover, the decreases in the numbers of local hospitals and non-hospital health care facilities in rural areas, small cities and towns might also push women in rural areas to be more likely to seek prenatal care in large hospitals. As to why such an effect started to emerge in the late 1990s rather than right after the launch of the NHI, it might be because the influences of the NHI payment scheme and of the dropping fertility on the structure and development of Taiwan's prenatal care market was not so strong in the first a few years of this insurance program, and became stronger a couple of years after the start of the NHI. With respect to such issues, there has been no study reported in the literature, and such research is worthy of more attention.

Given that women in rural areas were more likely to leave their living districts to acquire prenatal care in large hospitals in the late 1990s, it makes sense that women in rural areas were less likely to perceive improved convenience in transportation in the late 1990s than women in non-rural areas. Women in non-rural areas appeared to feel more convenient transportation in the 1990s than earlier in the 1990s. Since the number of health care facilities providing gynaecologic and obstetric care did not increase in the late 1990s, a possible reason for this improvement might be because of the improvements in public transportation systems in non-rural areas. For instance, Taiwan has started developing 'mass rapid transit systems' in large cities since the early 1990s. Therefore, it is reasonable that there would be an increased difference in estimation of convenience of transportation to and from prenatal care facility between women in rural areas and their counterparts living in non-rural areas in the late 1990s.

One more point deserving further exploration is whether choosing large hospitals for prenatal care was worth it for women. While our data could not show whether prenatal care services in large hospitals were worse than those offered in other settings, such as clinics and public health stations, some previous studies indicated that women seeking prenatal care in clinics were more likely to obtain adequate prenatal care than those seeking such care in hospitals one year after the NHI program started [6, 10]. Our study did not focus on 'measures for adequacy of prenatal care.' It would require further study to investigate the consequences of rural women's actions of leaving their local communities and going to large hospitals for prenatal care in the post-NHI period in terms of the quality of prenatal care received and the corresponding birth outcomes.

This study, which examined disparities between rural and non-rural areas, offers new information regarding the type of major health care facility used, and women's perception of the convenience of transportation for obtaining prenatal care. It discusses in detail the links of the trend in Taiwanese women's choice of prenatal care facility with developments in Taiwan's NHI, health care market, fertility and public transportation. It thus adds important information to the field of prenatal care. Our findings should be of particular use to Taiwan and countries with similar concerns and conditions for their future reforms in the delivery of prenatal care.

How to improve access to prenatal care in rural areas should be an important challenge. The literature has indicated that women who seek obstetrical care outside their local communities are more likely to have complicated deliveries, larger chances of prematurity, and more need for neonatal care for their children [26]. Previous research has also suggested that fewer pregnancy-related health services resource in rural areas adversely affects utilization of such health care in these areas [27]. Rural women are unavoidably facing higher risks for birth delivery, since they usually have to leave their community to deliver their children. Such a circumstance makes 'use of good quality prenatal care' even more essential for women in rural areas. While it does not seem efficient to increase the number of health care facilities offering prenatal care in rural areas, some other strategies should be seriously considered and tested. For instance, it should be helpful to improve the quality of prenatal care offered in rural public health stations by recruiting good gynaecologists and obstetricians to provide services in the health stations on a periodic and regular basis, and to construct a good referral system for prenatal care using public health stations as the base. It should also be helpful to provide rural women with more convenient transportation services to and from prenatal health care facilities. Furthermore, it should be helpful to disseminate health information on the importance of and the criteria for adequate prenatal care to help pregnant women make better choices regarding prenatal care.

This study focused on reporting results based on data for 1,575 children in the 4,820 available cases, as previously mentioned. The reason is that we concerned correlation among multiple cases from a same woman, since the two statistical models we used, the multinomial logit model and the ordered probit model, cannot not handle this kind of correlation problem. However, for the purpose of sensitivity analysis, we have also done analysis based on the 4,820 cases (results not shown). While more coefficients were statistically significant in results from analysing the 4,820 cases, these results do not conflict with conclusions we made with regard to comparison between rural and non-rural areas according to our results from analysing the 1,575 cases.

There are two main limitations for this study. The first pertains to recall bias, a problem inherent in most retrospective studies that make of surveys. Nonetheless, we believe that such recall bias in our study should not be serious. It has been shown that maternal recall of births five to seven years earlier is highly accurate, and maternal reports of prenatal events more than a decade after the birth are still reasonably accurate, especially events they directly participated in or information they have been told [28, 29, 30, 31]. The literature has also indicated that health care users can reliably report factual information such as the travelling time for obtaining ambulatory care [32]. Since most Taiwanese women only have one or two children and the recall period for this study is no more than ten years, it should not be hard for them to remember which health care facilities they used for prenatal care, and how they felt about the transportation to and from the facilities.

The second limitation is that our analysis only compared different cohorts of women giving births in the 1990s without controlling for some unobserved characteristics, such as attitudes and beliefs with regard to childbearing, prenatal care, and health care quality differences among different types of facilities. We were not able to further discuss how such characteristics that might vary among different cohorts of women might interact with the NHI influences on the prenatal care market, and subsequently result in changes in women's choice of prenatal care facilities. If we could also compare the experiences of prenatal care utilization for a specific cohort before and after the implementation of the NHI, we would be able to furnish more knowledge in this area.

Conclusion

In conclusion, we found that the women in rural areas were more likely to seek prenatal care in large hospitals, but were not more likely to perceive very convenient transportation to and from prenatal care facilities in the late 1990s than in the early 1990s. In contrast, women in non-rural areas did not have a stronger tendency to seek prenatal care in large hospitals in the late 1990s than in earlier periods. In addition, they did perceive an improvement in transportation for acquiring prenatal care in the late 1990s. More efforts should be undertaken to reduce these disparities and improve access to prenatal care of good quality in rural areas.

Competing interests

The author(s) declare that they have no competing interests.

Authors' contributions

Likwang Chen designed the study, led the data collection and statistical analysis, and drafted the manuscript. Chi-Liang Chen participated in designing the framework of statistical analysis and preparing the manuscript. Wei-Chih Yang participated in analyzing data analysis and preparing the manuscript. All authors read and approved the final manuscript.

Appendix

Formulas for calculating the 95% confidence interval estimates of changes corresponding to the three later periods in the 1990s

Changes in the Relative Probability of Choosing Hospitals from 1990-1992 to Later Years in the 1990s

The 95% confidence interval estimates of changes corresponding to the three later periods in the 1990s for non-rural areas were calculated as follows:

[math omitted]

For rural areas, the 95% confidence interval estimates for the three periods were respectively calculated as follows:

[math omitted]

Changes in the Probability of Perceiving Very Convenient Transportation from 1990-1992 to Later Years in the 1990s

In our model, there were three thresholds:

K1 , K2 , K3 . The 95% confidence interval estimates of changes in the probability of perceiving very convenient transportation corresponding to the three later periods for non-rural areas were respectively calculated as follows:

[math omitted]

[phi] is the density function of the standard normal distribution.

For rural areas, the three interval estimates were:

[math omitted]

References

1. Barros H, Tavares M, Rodrigues T:

Role of prenatal care in preterm birth and low birthweight in Portugal.J Public Health Med 1996, 18: 321-328.

2. Kogan MD, Martin JA, Ventura SJ, Alexander GR, Kotelchuck M, Frigoletto FD:

Benefits and limitations of prenatal care.[comment].JAMA : 280(24): 2071-2 1998 Dec 23-30; author reply 1998, 280 :2071-2072; author reply 2073.

3. Matthews Z, Diamond I:

Child immunisation in Ghana: the effects of family, location and social disparity.J Biosoc Sci 1997, 29: 327-343.

4. Bloom S, Lippeveld T, Wypij D:

Does antenatal care make a difference to safe delivery? A study in urban Uttar Pradesh, India.Health Policy Plan 1999, 14: 38-48.

5. Fiscella K:

Does prenatal care improve birth outcomes? A critical review.Obstet Gynecol 1995, 85: 468-479.

6. Chen CS, Liu TC, Chen LM:

National Health Insurance and the antenatal care use: a case in Taiwan.Health Policy 2003, 64: 99-112.

7. D'Ascoli PT, Alexander GR, Petersen DJ, Kogan MD:

Parental factors influencing patterns of prenatal care utilization.J Perinatol 1997, 17: 283-287.

8. Delvaux T, Buekens P, Godin I, Boutsen M:

Barriers to prenatal care in Europe.Am J Prev Med 2001, 21: 52-59.

9. Khoshnood B, Blondel B, de Vigan C, Breart G:

Socioeconomic barriers to informed decisionmaking regarding maternal serum screening for down syndrome: results of the French National Perinatal Survey of 1998.Am J Public Health 2004, 94: 484-491.

10. Liu TC, Chen CS:

The role of Taiwan's national health insurance program in influencing adequate prenatal care.Int J Health Plann Manage 2004, 19: 113-130.

11. Griffin JF, Hogan JW, Buechner JS, Leddy TM:

The effect of a Medicaid managed care program on the adequacy of prenatal care utilization in Rhode Island.Am J Public Health 1999, 89: 497-501.

12. Chen LM, Wen SW, Li CY:

The impact of national health insurance on the utilization of health care services by pregnant women: the case in Taiwan.Matern Child Health J 2001, 5: 35-42.

13. Chang TK, Li YM, Shaw CK:

The study of health care accessibility in remote areas of Hualien county after the launching of National Health Insurance Program.Tzu Chi Med J 1998, 10: 201-209.

14. Tseng WHR:

Family role on medical care among rural villagers in Taiwan.Proceedings of the First International Symposium on Families, East and West: 25-28 July 1991; Indianapolis 1991.

15. Poston DL, Gu B, Liu PP, McDaniel T:

Son preference and the sex ratio at birth in China: A provincial level analysis.Soc Biol 1997, 44: 55-76.

16. Liu T, Chen C, Tsai Y, Lin H:

Taiwan's high rate of cesarean births: Impacts of national health insurance and fetal gender preference.Birth 2007, 34: 115-122.

17. Greene WH:

Econometric Analysis 5 edition New Jersey: Prentice Hall Press; 2002.

18. Stata Corporation; :

Stata User's Guide Release 7. Texas 2001.

19. Hosmer DW, Lemeshow S:

Applied Logistic Regression New York: John Wiley & Sons Press; 1989.

20. Stata Corporation; :

Stata Reference H-P Release 7. Texas 2001.

21. Chang YS, Yaung CL:

The impact of NHI payment system on manpower among medical specialties in Taiwan.Chin J Public Health 1999, 18: 123-137.

22. Ministry of Interior; :

Taiwan's Demographic Fact Books Taiwan; various years from 1990 to 2005;.

23. Hong WH, Cheng SH, Chang RE, Chiang TL:

Changes in the proportion of cross-region admissions in Taiwan, 1985-1995.Chin J Public Health 1998, 17: 388-394.

24. Lu JR, Hsieh C:

An analysis of the market structure and development of Taiwan's hospital industry.Taiwan Econ Rev 2003, 31: 107-153.

25. Lin SJ, Yaung CL, Huang WF:

The influence of time cost on the utilization of ambulatory care among patients in a medical centre.Chin J Public Health 1997, 16: 319-328.

26. Nesbitt TS, Connell FA, Hart LG, Rosenblatt R:

Access to obstetric care in rural areas: effect on birth outcomes.Am J of Public Health 1990, 80: 814-818.

27. Burgard S:

Race and pregnancy-related care in Brazil and South Africa.Soc Sci Med 2004, 59: 1127-1146.

28. Githens PB, Glass CA, Sloan FA, Entman SS:

Maternal recall and medical records: an examination of events during pregnancy, childbirth, and early infancy.Birth 1993, 20: 136-141.

29. Tilley BC, Barnes AB, Bergstralh E, LaBarthe D, Noller KL, Colton T, Adam E:

A comparison of pregnancy history recall and medical records.Am J Epidemiol 1985, 121: 269-281.

30. Yawna BP, Sumanb VJ, Jacobsenc SJ:

Maternal Recall of Distant Pregnancy Events.J Clin Epidemiol 1998, 51: 399-405.

31. Tomeo CA, Rich-Edwards JW, Michels KB, Berkey CS, Hunter DJ, Frazier AL, Willett WC, Buka SL:

Reproducibility and validity of maternal recall of pregnancy-related events.Epidemiology 1999, 10: 774-777.

32. Brown JB, Adams ME:

Patients as reliable reporters of medical care process: recall of ambulatory encounter events.Med Care 1992, 30: 400-411.

Author Affiliation:

[1] Centre for Health Policy Research and Development, National Health Research Institutes, No.35 Keyan Road, Zhunan Town, Miaoli County 350, Taiwan

[2] Institute of Public Health & Department of Social Medicine, School of Medicine, National Yang-Ming University, Taipei City 112, Taiwan

[3] The Department of Accounting, The College of Business, Chung Yuan Christian University, Chung-Li City, Taoyuan County 320, Taiwan

[4] Department of Accounting, College of Management, National Taiwan University, Taipei City 106, Taiwan

Author Email: Likwang Chen - likwang@nhri.org.tw; Chi-Liang Chen - d90722002@ntu.edu.tw; Wei-Chih Yang - weichih@nhri.org.tw

Article history:

Received Date: 3/6/2007

Accepted Date: 3/29/2008

Published Date: 3/29/2008

Article notes:

� 2008 Chen et al; licensee BioMed Central Ltd.

Health Insurance as a New Indicator of Farm Households' Well-Being - Amber Waves

As with all households, the basic indicators of farm household well-being-income and wealth-do not fully capture information about well-being, Because medical care is relatively expensive and can significantly affect morbidity and mortality, the incidence of health insurance coverage among populations is an important indicator of well-being, Since farming is a relatively dangerous occupation, health insurance coverage is critical, Health insurance provides individuals or groups with a contractual arrangement for personal medical expenses to be covered (usually, in part) in exchange for a fee paid to insurance companies.

Most Americans receive health insurance coverage through employer-sponsored programs, Farmers are generally self-employed, raising the possibility that farm households might be less likely to have health insurance, However, USDA's 2006 Agricultural Resource Management Survey (ARMS) data clearly show that individuals in farm operator households are, in fact, somewhat more likely to have health insurance coverage than the general U.S. population, The Bureau of the Census reports that 84.2 percent of the U.S. population had some form of health insurance for any part of 2006, compared with 86,2 percent of the members of farm operator households.

Although farmers are largely self-employed, the operator and/or spouse also are employed off the farm in two-thirds of farm households, As with the general population, the most common source of health insurance for members of farm households is employment-based, In fact, farm household members are almost as likely as the general U.S. population to receive health insurance through an outside employer.

Farm households without the operator or spouse working at a nonfarm job are the least likely to have health insurance, However, these farm operator households are more likely to be elderly and, consequently, are often eligible to receive health insurance from a government program-virtually all U.S. citizens age 65 or older have some coverage through Medicare, Some households in which neither the operator nor the spouse works off the farm have employment-based health insurance coverage from previous nonfarm employers or as employees of their own farm businesses.

Farm households with large operations (with sales of $250,000 or more), because they are more fully employed on the farm, are less likely to have an operator or spouse working off the farm than other farm households, Large-farm households are more likely to purchase health insurance directly from an insurance provider.

The indicators of health insurance coverage provide more evidence of the strong links between farm household well-being and the nonfarm economy, The average farm household receives 85 percent of its income from off-farm sources, and off-farm work has become the major source of health insurance coverage, These new indicators show that the farm population generally has found the means to acquire health insurance.

This finding is drawn from...

ERS Briefing Room on Farm Household Economics and Well-Being, www.ers.usda.gov/briefing/wellbeing/

[Author Affiliation]

FARMERS RECEIVE HEALTH SERVICES THROUGH EAST CAROLINA UNIVERSITY AGRISAFE-NORTH CAROLINA - US Fed News Service, Including US State News

GREENVILLE, N.C., Jan. 15 -- East Carolina University issued the following press release:

They work in one of the most dangerous professions in North Carolina, yet about 27 percent of the state's agricultural families do not have health insurance, according to research by the North Carolina Agromedicine Institute at East Carolina University and the Cecil G. Sheps Center for Health Services Research.

Many farmers must choose between paying for farm operations and paying for health insurance, which can cost as much as $500 to $1200 per individual. And if farmers do visit a doctor's office, their physician may not consider the unique occupational hazards they face, such as skin cancer, respiratory illness, arthritis and mental health disorders, said Robin Tutor, interim director of the N.C. Agromedicine Institute.

'We all enjoy farmers' products every day. We eat them; we wear them. These people provide us with so much, so we need to serve our farmers in return,' Tutor said.

In an effort to improve health for farmers and their families, the institute has brought AgriSafe-North Carolina, a program that provides agricultural occupational health and safety screenings at low to no-cost, to eastern North Carolina.

Through AgriSafe-NC, the institute partners with Tri-County Community Health Council to provide health screenings and follow-up health services for farmers, their families and non-migrant farm workers. Services are provided at the Carolina Oaks Health Center in Four Oaks or at other locations convenient for the individual such as a farm, agribusiness, Cooperative Extension office or other community location.

'We want to be as accessible as possible,' Tutor said.

AgriSafe staff includes a family nurse practitioner, community outreach worker and family advocate. Services include health care with an emphasis on agricultural exposures, as well as education and outreach to prevent illness and injury on the farm. Staff can help to identify resources for affordable dental care, medications, diabetic supplies and dealing with family challenges. Farmers can also select and be fitted with personal protective equipment such as respirators, safety glasses, hearing protection and chemical resistant clothing for the prevention of injury and illness.

Tutor called this a 'one-stop shop.' 'We want to look at the farm family's total wellbeing, not just their physical wellbeing. We want to address the whole person,' she said. 'And we recognize that farmers have unique demands on their time and resources.' Carolina Oaks is open five days a week. Evening and weekend appointments at the clinic or in the community can also be arranged. Fees vary depending on services received and where services are rendered. Many services are provided at a free or reduced cost.

The AgriSafe Network started in Iowa, where it has been successful in reducing health insurance claims costs for farmers. A $100,000 grant from the Kate B. Reynolds Charitable Trust Foundation funded the one-year pilot program in eastern North Carolina, targeting Bladen, Columbus, Cumberland, Duplin, Harnett, Johnston, Pender, Robeson, Sampson and Wayne counties.

Funding will continue through March, and Tutor said the institute is actively seeking new partners among agribusinesses and non-profit foundations to keep the program going.

For more information about AgriSafe or to request services, call the North Carolina Agromedicine Institute at 252-744-1000 or Carolina Oaks Family Health Center at 919-963-6400.For more information about US Fed News contract awards please contact: Sarabjit Jagirdar, US Fed News, Email:- htsyndication@hindustantimes.com.

Health insurance of rural/township schoolchildren in Pinggu, Beijing: coverage rate, determinants, disparities, and sustainability.(Research)(Report) - International Journal for Equity in Health

Authors: Jane M Zhu (corresponding author) [1,2,3]; Yiliang Zhu [4]; Rui Liu [5,6]

Background

By the 1970s, nearly all urban Chinese population and 85% rural residents were covered under a health insurance scheme[1]. Market-oriented reform in the following decades witnessed the disintegration of the healthcare system and the disappearance of the public insurance systems[2]. By 2003, insurance coverage fell to 54-55% in urban population with only 12% of the poorest fifth covered[3, 4], while 79% (640 million) rural residents were without insurance due to the dissolution of agricultural communes that had served as the primary payer[2, 3, 5]. In the meantime, out-of-pocket medical costs climbed steadily[2, 6], healthcare utilization declined[3], and barriers to healthcare rose, particularly for the poor and the rural [7, 8].

In 1998 the Chinese government began to establish a basic health insurance scheme (BHIS) for registered urban workers and retirees[9]. The cooperative BHIS does not, however, cover children or other dependents[9, 10]. In 1994 the government began to pilot a new rural cooperative medical system (RCMS) in rural areas[11], expanding the program to 310 counties by 2004[5, 12] and aiming to cover the entire rural population by 2010. Only farmers are eligible for RCMS and enrollment is voluntary in unit of a household. As of 2006, households, local, and central governments each contributed no less than 20 yuan (RMB) per enrollee[13]. Amid these fundamental reforms, health insurance access and coverage of schoolchildren is largely unknown[8]. Except for a few earlier studies on children's health insurance coverage using data from the China Health and Nutrition Survey prior to 1997[6, 8], studies on healthcare access, outcomes, and disparities between urban and rural populations generally have not examined children [14, 15, 16]. For instance, the 2003 Third National Health Services Survey (NHSS) remained non-specific to the country's 270 million children[3]; another study by Xu et al [4] only considered age-group insurance coverage for urban population based on the 2003 NHSS data.

As China adopts national and regional cooperative schemes to re-establish a national health insurance system, achieving and sustaining a high enrollment rate are a benchmark for program success. It is thus critical to identify barriers to enrollment, uncover disparities among rural and urban populations, and evaluate perceived and tangible benefits of existing cooperative schemes. Based on a survey of elementary schoolchildren, this paper focuses on disparate health insurance coverage among farmers' and non-farmers' children, along with their access to and utilization of healthcare under various insurance schemes. It also discusses potential threats to sustainable insurance enrollment, and recommends measures for program improvement.

Methods

Study Setting

Pinggu is a mountainous district in eastern Beijing; over 75% of its 397,000 residents are farmers and 60% of land area agricultural. The area represents a growing segment of rural China that is in close proximity to major cities and is undergoing rapid socioeconomic transition. The BHIS was established there in 2001 and the RCMS in 2004. Beginning in the 1990s, a

Student Safety and Health Insurance (SSHI) program was introduced through local school administrations in partnership with commercial vendors. The SSHI charges an annual premium of 60 to a hundred some yuan (RMB), reimburses partially medical expenses incurring from major events such as surgery and hospitalization. In September 2004, the local Red Cross, municipal Education Commission, and Bureau of Hygiene and Health jointly established a Children's Hospitalization Cooperative Fund (CHCF), which offers a not-for-profit, cooperative scheme to all local schoolchildren. At a 50-yuan annual premium, CHCF progressively covers up to 50% medical expenses, with a cap of 80,000 yuan/year, for hospitalization, surgery, and special treatments such as chemotherapy and dialysis. Schoolchildren thus have choices among SSHI, CHCF, RCMS, or commercial schemes.

Survey

Four primary schools were selected from 108 by Pinggu's Education Bureau. All first and fourth graders were invited. A questionnaire was distributed in class, and filled by a parent or guardian of each class-attending student. Of 611 questionnaires distributed, 490 (80%) were returned. The questionnaire collected demographic and socioeconomic information, child's health status, insurance coverage, healthcare access and utilization, and parental perceptions of the health insurance system and healthcare system. Data on insurance included the child's insurance status, history, premium, and benefits. Parental perception about insurance and healthcare systems consisted of satisfaction, expectations of service, and perceived barriers.

Statistical Analysis

S-Plus 6.2

[R] (Insightful, Seattle) was used for analysis. Descriptive statistics for selected demographic factors and their association with insurance status were reported. Adjusted odds ratios via logistic regression, their confidence interval, and likelihood ratio tests were calculated to evaluate potential determinants to insurance coverage. Disparities in care access and utilization between farmers' and non-farmers' children were analyzed through chi-squared tests.

Results

Sample Characteristics

Table 1 summarizes household characteristics. Of 494 participating children in total, including four pairs of twins, 55.0% (n = 260) were female and 45.0% (n = 213) were male, 21 did not report gender. There were 319 (66.0%) one-child households, while 164 (34.0%) households had two or more children. The sample children were generally healthy, with 88.6% of parents reporting children in very good or excellent health.

Table 1 caption: Children's Characteristics and Health Insurance Status [table omitted]

Farming was the single-most common occupation, with 34.5% (n = 164) households having two farming-parents, and 6.5% (n = 31) households having one farming-parent, respectively. About 11% (n = 53) households had at least one unemployed parent. Fifteen percent households had annual incomes over 35,000 yuan, but three-quarters of both-farmer-parent households earned 10,000 yuan or less. The majority of household heads (60.7%) had completed high school or beyond, and over half (53.1%) reported having health insurance of their own.

Rate of Insurance Coverage and Determinants

Overall, 54% (n = 249) children had some type of health insurance, although the coverage was uneven across a number of factors (table 1). Decisions to buy insurance for a child was not associated with gender (p = 0.79), age (p = 0.50), or general health (p = 0.14). Household per capita income did not significantly influence the decision either (p = 0.12). However, children of an insured parent were more than twice as likely to have insurance as those of uninsured parents (74% vs. 33%, p < 0.001). Households of 1-2 children were more likely to have insurance for the participating child than those with more children (53% vs. 30%, p = 0.012). While only 33% of households in the lowest education group enrolled their children in an insurance program, the rate rose steadily to 63% among households in the post-secondary education group (p = 0.002). Interestingly, the coverage rate among farming households (with at least one farming parent) was comparable to that of government/state enterprise employed parents (58% vs. 61%), but higher than households of other occupations.

The decision to enroll a child in an insurance scheme results from the interplay of healthcare need and cost-benefit considerations. We used a logistic regression model to evaluate the impact of potential surrogates of cost and benefit on the decision to enroll, and present adjusted odds ratios (OR) for insurance in Table 2. On the affordability (cost) end, families with 3+ children were only 38% as likely to have insurance for a child as families with 1-2 children (OR = 0.38, CI = 0.11-1.40, p = 0.002); farmer's households (OR = 7.22) and those with an unemployed parent (OR = 2.57) were more likely to buy insurance than households of non-unemployed, non-farmer parents (p-value = 0.03). It is noteworthy that the rate of coverage among households that perceived insurance to be affordable was comparable to that among households unable to afford insurance (OR = 1.07). In contrast, households with neutral perceptions about insurance affordability or just somewhat positive were much less likely to have insurance (OR = 0.47, 0.65, respectively, p < 0.001). On the perceived 'benefit' end, children of uninsured parents were much less likely to have insurance than those with an insured parent (OR = 0.01, p < 0.001); parents who had positive opinion about the insurance system were more than 3 times as likely to buy insurance for the child as those who one level less positive in terms of satisfaction ('dissatisfied', 'neutral/somewhat satisfied', 'satisfied') (OR = 3.17, p < 0.001). Parental educational level, as a multi-faceted factor related to affordability, as well as knowledge and perceptions about insurance, did not influence a child's insurance status if the parent was also insured, but played a promotional role if the parent was uninsured: parents of a given level of education were 2.59 times as likely to enroll a child as their counterpart whose education was one level lower (OR = 2.59, p-value < 0.001).

Table 2 caption: Determinants of and Barriers to Children's Health Insurance [table omitted]

Disparity in Coverage

Although disparity in children's coverage was muted between farmers and non-farmers' households, it existed with respect to the type of insurance programs. Compared with low-premium schemes RCMS, CHCF, and SSHI, commercial policies required an annual premium as high as 10,000 yuan, with a median of 1,000 yuan. Farmers' children were enrolled overwhelmingly in low-premium schemes (i.e. RCMS, CHCF, or SSHI), rather than commercial options (75.7% vs. 24.3%); in contrast, 58% and 40% of children in the 'non-farmer & employed' and 'non-farmer & unemployed' occupational groups, respectively, were covered under a commercial policy ([chi]

2 = 25.3, p = 0, Table 3).Table 3 caption: Primary Insurance Scheme1 by Parental Occupation2 [table omitted]

Care Access and Utilization

Did insurance coverage, particularly the cooperative, low-premium schemes, improve schoolchildren's access to and utilization of care? Table 4 presents results from our comparison of three groups: uninsured, insured under low-premium schemes, and insured under commercial schemes. We found that insurance coverage generally improved access to care. Among the group covered under a low-premium or cooperative scheme, 43% parents perceived little difficulty in healthcare access compared with 15% who had difficulty; among parents whose child was under a commercial scheme, the percentage was 51% vs. 8%; for uninsured children, only 24% of parents perceived no difficulty, while 17% did. This pronounced difference (p < 0.001) suggested that both commercial and cooperative schemes improved parental perceptions of healthcare access. However, 24% parents whose children were enrolled in a low-premium scheme felt healthcare to be unaffordable, compared with 14% and 18% under commercial schemes and uninsured, respectively. Conversely, 58%, 62%, and 52% of parents in the low-premium, commercial, and uninsured groups, respectively, felt healthcare to be affordable. These group differences (p = 0.08) implied that the low-premium schemes only provided limited relief of financial burden despite perceptions of improved access.

Table 4 caption: Disparities in Healthcare Access and Utilization [table omitted]

These differential perceptions of access and affordability were also mirrored in the incidence of delayed or forgone care. When ill, 13.2% children under a low-premium scheme delayed care-seeking, compared with 17.9% of those under a commercial scheme and 23.6% of the uninsured. When comparing only the low-premium group with the uninsured, the difference in delayed care was more statistically pronounced (p = 0.05). Similarly, compared to the uninsured, children under a low-premium or commercial plan were less likely to forego care when ill (14.3% and 11.5% vs. 24.5%, p = 0.009). Because the three groups of children were generally healthy and similar in baseline health, the differences in health-seeking behaviors were likely attributable to the security afforded by insurance. However, as indicated by self-reported 12-month outpatient visitation data, care utilization patterns did not differ among the three groups (p = 0.796, Table 4). This observation suggests that the existing insurance schemes did not translate perceived improvements in access and affordability into improved care utilization, because most schemes did not alleviate the financial burden associated with routine care. On a positive note, overall satisfaction with healthcare was significantly higher among parents of an insured child than their uninsured counterparts (p = 0.01), with no marked difference between the low-premium and commercial insurance groups.

Barriers to Enrollment

To further understand barriers to enrollment to and sustainability for cooperative programs, we probed parental concerns regarding children's insurance specifically and the existing insurance system in general. Table 5 shows that parents of an insured child were three times as likely to be positive about the insurance system as those of an uninsured child (48% vs. 16%), and that they were much less likely to be dissatisfied (13% vs. 31%). The difference suggested that direct experience with health insurance reinforced a better understanding and more positive opinion of the insurance system. However, leading concerns about insurance were rather similar among the three groups. High cost, followed by limited benefits, was the leading concern among over half of parents whose children either were uninsured or participated in a low-premium scheme. Although over half of the uninsured group were willing to enroll if the cost was low enough (58%) or if benefits improved (50%), only 3.7% in this group viewed health insurance as a necessity, underlining some fundamental barriers to insurance enrollment. Lack of knowledge about insurance appeared to be another barrier. Among those whose child was covered under a low-premium scheme, 4.3% indicated a lack of insurance knowledge; but this rate was three times as high among parents with an uninsured child. Distrust of business practice, lack of government oversight, and poor service quality were among other parental concerns about the insurance system.

Table 5 caption: Surrogate Barriers to Insurance [table omitted]

Discussion

This survey shows that health insurance coverage for schoolchildren in Pinggu had risen in two waves, from 14% in 1999 to 44% in 2003, and to 54% in 2005. Commercial policies were the main vehicle prior to 1999; SSHI drove the first wave during 2000-2003; CHCF and RCMS later became major players, nearly doubling insurance rate among farmers' children. Although greater than a 1997 estimate of 20%[8] and a 2003 estimate of 43%[4], the current coverage rate of 54% remained low. Because of the high costs, commercial schemes remained unaffordable for most low and moderate income households, especially farming households. As a result, farmers' children largely depended on low-premium and cooperative schemes for insurance coverage that does not provide benefits for routine healthcare and are also low in reimbursement for covered medical events. While cooperative schemes such as RCMS and CHCF are becoming the principle insurance vehicle for schoolchildren, overlapping among these low-premium schemes in coverage, benefits, cost-reimbursement structure forces enrollees to choose one scheme over another. This was likely one reason why only 10% of insured farmers' children were under the RCMS, compared with 51% in the SSHI and 14% in the CHCF.

Perceived affordability played a delicate role in purchasing schoolchildren's health insurance. It is puzzling that those who appeared least or most able to afford insurance were more likely to enroll than their counterparts who were somewhat able to afford insurance. One explanation is that the somewhat-affordable may feel that the limited benefit options were unworthy of the premium even if it is low, whereas the unaffordable may value the basic protection against catastrophic events. This explanation echoes the argument of Chernew

et al .[17] that universal coverage may not be achievable by reducing premiums alone. A recent study of villagers in Guizhou province China reports that 29% of the participants did not enroll in RCMS even when given a subsidy for the premium[18]. Low premiums may make insurance schemes more affordable, but narrow benefits may make them less practical, thereby dampening consumers' willingness-to-pay. For enrollees in cooperative schemes, substantial out-of-pocket co-payments have been found to be necessary in order to sustain the programs[19], thus adversely affecting healthcare access and diminishing the value of insurance policies[19, 20]. Findings from this study reflected this phenomenon.

Our analysis suggests that by affording the enrollees a sense of security, the existing insurance schemes had improved perceived care access and affordability, and had also reduced delayed or forgone care. These improvements among those with a low premium policy over those uninsured were especially attributable to having insurance because insurance enrollment was neither driven by poor health nor promoted by a low premium. Insured children did not utilize more outpatient care than uninsured children, however, confirming that the existing insurance schemes did not alleviate the financial burden for routine care, and were ineffective in improving overall affordability. This argument is further supported by our findings that large portions of the insured under a low-premium scheme remained less positive about their access to and affordability of healthcare (57% and 42%, respectively).

The World Bank reported that in 2003 total contribution to the new RCMS from all sources covered only 20% of total household healthcare spending among enrolled Chinese farming households[5]. If enrollment to the cooperative schemes remains low, the programs may face adverse selection among enrollees and a shrinking pool of funds, which could threaten program sustainability and expansion[5, 21]. Thus improving tangible benefits is essential for sustaining and expanding enrollment. A recent analysis argued that better benefits and reimbursement with more government funding are necessary for the RCMS to sustain in less developed rural areas[19]. A second study found that a considerable number of urban residents (24%) were actually willing to buy a commercial policy to compensate for outpatient care expense[22]. Still another study showed that both willingness-to-pay and actual amount contributed for enrolling to the BHIS increased with added benefits[23]. Offering more benefit options with flexible premiums within the existing cooperative programs would allow consumers to choose policies to fit their needs and increase willingness-to-pay, thereby boosting program enrollment.

We observed that compared to their uninsured counterparts, parents themselves insured were an order of magnitude more likely to enroll their children, and once enrolled were two times more satisfied with the insurance system. In a study of U.S. parents, Guendelman and Pearl[24] also observed that positive parental experiences with and improved knowledge about health insurance system promoted children's access to insurance. It is likely that consumers' experience with and perception about health insurance reinforce one another, and adequate knowledge about insurance promotes positive experience and mediates perception. Thus, community outreach could be an effective means for educating parents about children's health insurance, therefore promoting children's insurance enrollment.

There is currently no national health insurance program designated for schoolchildren, making them vulnerable in securing access to healthcare. In response to this systemic gap, regional programs have been emerging in parts of China, forming essentially a second tier of schemes to cover schoolchildren. However, vast disparities in regional economic development and variations in healthcare needs underscore the gap between the existing monolithic system and variable healthcare needs. To address this challenge requires innovative strategies on the part of the government and industry. One feasible approach is to expand the second-tier regional programs such as the CHCF, in conjunction with commercial programs to supplement the national schemes.

Conclusion

The overwhelming choice of cooperative and low-premium insurance schemes among farmer's children reflected both their need for protection against major medical events and their willingness-to-pay or their affordability. Although these cooperative schemes did not fully meet schoolchildren's healthcare needs, especially with respect to routine care, they nonetheless positively impacted on perceived access to and affordability of healthcare, reduced undesirable health-seeking behaviors, and improved overall satisfaction with healthcare.

To increase the tangible value of existing health insurance programs, it is both necessary and feasible to offer more insurance options through expanding the national programs such as the RCMS or by developing second-tier, regional programs such as the CHCF to help cover routine healthcare needs.

Government should play a central role in funding and guiding national and regional health insurance programs, while simultaneously strengthen regulation of the health insurance market. Improved government oversight is not only high in consumer demand, but also will enhance consumer confidence in the healthcare system.

Improving parental knowledge about health insurance can help increase schoolchildren's insurance enrollment. The success of SSHI, by means of partnerships with school administrations, demonstrates that community outreach can be a highly effective marketing tool in educating the parents about children's health insurance.

Despite the small scale and specific scope of this study, our findings are relevant on a much larger scale, as Pinggu represents a large segment of Chinese rural/suburban townships. Findings from this study fill an important information gap for schoolchildren, are useful in guiding future evaluation of health insurance coverage, but need to be replicated on a larger scale. Evaluation of China's evolving healthcare needs and healthcare outcomes should be conducted on an ongoing basis. Integrating the evaluation of schoolchildren's insurance into this process by utilizing national resources such as the National Health Services Survey appears both attractive and feasible.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

JMZ participated in the conception, design, and conduct of this study. She led the efforts in the development of instruments, data collection, analysis, and draft of the paper. YZ participated in the conception and design of the study, development of the instruments, conducting data analysis, and the writing of the article. RL participated in the design, implementation, and conducting of the study. All read and approved the content of this paper.

References

1. World Bank; :

China 2020, issues and options for China: Financing health care Washington DC; 1997.

2. World Bank; :

China's health sector: Why reform is needed.Rural Health in China. Briefing Note Series, Briefing Note No. 3 Washington, DC; 2005.

3.

Ministry of Health People's Republic of China.Third National Health Services Survey: Report on main results 2004: [http://www.moh.gov.cn/publicfiles/business/htmlfiles/mohwsbwstjxxzx/s856 1/200809/37882.htm].

4. Xu L, Wang Y, Collins CD, Tang S:

Urban health insurance reform and coverage in China using data from National Health Services Surveys in 1998 and 2003.BMC Health Services Research 2007, 7: 37.

5. World Bank; :

Rural health insurance: Rising to the challenge. Rural Health in China.Briefing Note Series, Briefing Note No. 6 Washington, DC; 2005.

6. Akin JS, Dow WH, Lance PM:

Did the distribution of health insurance in China continue to grow less equitable in the nineties? Results from a longitudinal survey.Social Science & Medicine 2004, 58: 293-304.

7. Gao J, Tang S, Tolhurst R, Rao K:

Changing access to health services in urban China: implications for equity.Health Policy and Planning 2001, 16: 302-312.

8. Adams J, Hannum E:

Children's social welfare in China, 1989-1997: Access to health insurance and education.China Quarterly 2005, 181: 100-121.

9. Beijing Municipal Government; :

Provisions on Basic Medical Insurance of Beijing Municipality, Order #68. 2001: [http://www.lawinfochina.com/law/display.asp?id=4327].

10. Liu YL:

Reforming China's urban health insurance system.Health Policy 2002, 60: 133-150.

11. Carrin G, Ron A, Hui Y, Hong W, Zhang T, et al:

The reform of the rural cooperative medical system in the People's Republic of China: interim experience in 14 pilot counties.Social Science & Medicine 1999, 48: 961-972.

12. Mao ZZ:

Pilot program of NCMS in China: System design and progress.World Bank Report on China Rural Health Study 2005: [http://siteresources.worldbank.org/INTEAPREGTOPHEANUT/Resources/502734-1129734318233/NCMS-report-revisedversion.pdf].

13.

Ministry of Health People's Republic of China. Document No. 13. 2006: [http://www.gov.cn/xwfb/2006-07/10/content_331858.htm].

14. Akin JS, Dow WH, Lance PM, Loh CPA:

Changes in access to healthcare in China: 1989-1997.Health Policy & Planning 2005, 20: 80-89.

15. Blumenthal D, Hsiao W:

Privatization and its discontents: the evolving Chinese health care system.New England Journal of Medicine 2005, 353(11): 1165-1170.

16. Liu M, Zhang Q, Lu M, Churl-Su Kwon C-S, Quan H:

Rural and urban disparity in health services utilization in China.Medical Care 2007, 45: 767-774.

17. Chernew M, Frick K, McLaughlin CG:

The demand for health insurance coverage by low-income workers: Can reduced premiums achieve full coverage?.Health Services Research 1997, 32: 453-471.

18. Zhang L, Wang H, Wang L, Hsiao W:

Social capital and farmers' willingness to join a newly established community-based health insurance in rural China.Health Policy 2006, 76: 233-242.

19. Dib HH, Pan X, Zhang H:

Evaluation of the new rural cooperative medical system in China: Is it working or not?.International Journal for Equity in Health 2008, 7: 17.

20. Wang H, Yip H, Zhang L, Wang L, Hsiao W:

Community-based health insurance in poor rural China: the distribution of net benefits.Health Policy and Planning 2007, 20(6): 366-374.

21. Wang H, Zhang L, Yip H, Hsiao W:

Adverse selection in a voluntary Rural Mutual Health Care health insurance scheme in China.Social Science and Medicine 2006, 63: 1236-1245.

22. Ying X-H, Hu T-W, Ren J, Chen W, Xu K, Huang J-H:

Demand for Private Health Insurance in Chinese Urban Areas.Health Economics 2007, 16: 1041-1050.

23. B�rnighausen T, Liu Y, Zhang X, Sauerborn R:

Willingness to pay for social health insurance among informal sector workers in Wuhan, China: a contingent valuation study.BMC Health Services Research 2007, 7: 114.

24. Guendelman S, Pearl M:

Children's ability to access and use health care.Health Affairs 2007, 23(2): 235-244.

Author Affiliation:

[1] Harvard Medical School, 260 Longwood Ave, Rm. 233 Boston, MA 02115, USA

[2] Sanford Institute of Public Policy, Duke University, P.O. Box 99712, Durham, NC 27708, USA

[3] Formally: Fudan University School of Public Health, Shanghai, PR China

[4] Department of Epidemiology and Biostatistics, College of Public Health, University of South Florida, 13201 Bruce B. Downs Blvd. MDC 56, Tampa, Florida 33612-3805, USA

[5] Health Services and Policy Analysis, 140 Warren Hall #7360, University of California-Berkeley, Berkeley, California 94720, USA

[6] Formally: Beijing University Guanghua School of Management, Haidian District, Beijing, 100871, PR China

Author Email: Jane M Zhu - jane_zhu@hms.harvard.edu; Yiliang Zhu - yzhu@health.usf.edu; Rui Liu - liur@gsm.pku.edu.cn

Article history:

Received Date: 8/1/2008

Accepted Date: 11/3/2008

Published Date: 11/3/2008

Article notes:

� 2008 Zhu et al; licensee BioMed Central Ltd.